Transfer of reinforcement learning: the state of the art

被引：0
|
作者：
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing 210093, China [1 ]
机构：
来源：
Tien Tzu Hsueh Pao | 2008年 / SUPPL.卷 / 39-43期
关键词：
Reinforcement learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Deep Reinforcement Learning: A State-of-the-Art Walkthrough
    Lazaridis, Aristotelis
    Fachantidis, Anestis
    Vlahavas, Ioannis
    JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2020, 69 : 1421 - 1471
  • [2] Explainable Deep Reinforcement Learning: State of the Art and Challenges
    Vouros, George A.
    ACM COMPUTING SURVEYS, 2023, 55 (05)
  • [3] Reinforcement learning applied to machine vision: state of the art
    A. M. Hafiz
    S. A. Parah
    R. A. Bhat
    International Journal of Multimedia Information Retrieval, 2021, 10 : 71 - 82
  • [4] Reinforcement learning applied to machine vision: state of the art
    Hafiz, A. M.
    Parah, S. A.
    Bhat, R. A.
    INTERNATIONAL JOURNAL OF MULTIMEDIA INFORMATION RETRIEVAL, 2021, 10 (02) : 71 - 82
  • [5] Causality in Reinforcement Learning Control: The State of the Art and Prospects
    Sun Y.-W.
    Liu W.-Z.
    Sun C.-Y.
    Zidonghua Xuebao/Acta Automatica Sinica, 2023, 49 (03): : 661 - 677
  • [6] Deep reinforcement learning: A state-of-the-art walkthrough
    Lazaridis A.
    Fachantidis A.
    Vlahavas I.
    Journal of Artificial Intelligence Research, 2021, 69 : 1421 - 1471
  • [7] Drone Landing and Reinforcement Learning: State-of-Art, Challenges and Opportunities
    Amendola, Jose
    Cenkeramaddi, Linga Reddy
    Jha, Ajit
    IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 5 : 520 - 539
  • [8] State of the Art Control of Atari Games Using Shallow Reinforcement Learning
    Liang, Yitao
    Machado, Marlos C.
    Talvitie, Erik
    Bowling, Michael
    AAMAS'16: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS, 2016, : 485 - 493
  • [9] ART-R: A novel reinforcement learning algorithm using an art module for state representation
    Brignone, L
    Howarth, M
    2003 IEEE XIII WORKSHOP ON NEURAL NETWORKS FOR SIGNAL PROCESSING - NNSP'03, 2003, : 829 - 838
  • [10] Transfer Learning in Deep Reinforcement Learning
    Islam, Tariqul
    Abid, Dm. Mehedi Hasan
    Rahman, Tanvir
    Zaman, Zahura
    Mia, Kausar
    Hossain, Ramim
    PROCEEDINGS OF SEVENTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, ICICT 2022, VOL 1, 2023, 447 : 145 - 153
12345